Using `VectorMath::DotProduct()` in GatedRecurrentLayer to reuse existing
SIMD optimizations. Results:
- When SSE2/AVX2 is avilable, the GRU layer takes 40% of the unoptimized
code
- The realtime factor for the VAD improved as follows
- SSE2: from 570x to 630x
- AVX2: from 610x to 680x
This CL also improved the GRU layer benchmark by (i) benchmarking a GRU
layer havibng the same size of that used in the VAD and (ii) by prefetching
a long input sequence.
Bug: webrtc:10480
Change-Id: I9716b15661e4c6b81592b4cf7c172d90e41b5223
Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/195545
Reviewed-by: Per Åhgren <peah@webrtc.org>
Commit-Queue: Alessio Bazzica <alessiob@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#32803}
Refactoring done to more easily and cleanly add SIMD optimizations and
to remove `GatedRecurrentLayer` from the RNN VAD api.
Bug: webrtc:10480
Change-Id: Ie1dffdd9b19c57c03a0b634f6818c0780456a66c
Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/195445
Commit-Queue: Alessio Bazzica <alessiob@webrtc.org>
Reviewed-by: Jakob Ivarsson <jakobi@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#32770}
